Acceleration data is seen as a key reporting element for insurance companies. For those applications that the accelerometer is installed freely in different vehicles, a reliable algorithm is required to automatically calibrate and normalize the accelerometer values in order to have accurate longitudinal and lateral accelerations regardless of device orientation within the vehicle. The device is often self-installed by the user in an unknown orientation relative to the vehicle. This algorithm is to require no human intervention to perform calibration.
Much of the related previous work has focused on estimation of the accelerometer orientation for body-worn devices. In one, the gravity vector is used to estimate the vertical component and the magnitude of the horizontal component of the user's motion for a free oriented 3-axis accelerometer system. This method estimates the magnitude of the horizontal component and fails to determine its orientation. Another extends the work to estimate orientation of a 3-axis accelerometer within the horizontal plane for the users who carry such devices. Limiting the user to walk forward in a fairly straight direction, it applies the Principal Component Analysis (PCA) to infer the orientation in horizontal plane.